Alon Y. Levy and Marie-Christine Rousset. Combining horn rules and description logics in CARIN. Artificial Intelligence, 104:165--209, 1998.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....of the KR concept definition. Queries can be compared using query containment algorithms. There is a detailed literature that studies the differences between the expressive power of description logics and query languages and the complexity of the subsumption and containment problem for them (e.g. [21]) For example, certain forms of negation and number restrictions, when present in query expressions, make query containment undecidable, while arbitrary join conditions cannot be expressed and reasoned about in description logics. Many different types of semantic mappings are required in ....

A. Levy and M.-C. Rousset. Combining Horn rules and description logics in carin. Artificial Intelligence, 104:165--209, September 1998.

....a first experiment: learning Carin ALN rules with the ILP system Cilgg from the standard ILP Mesh Design dataset. Accepted to appear in: S. Matwin, C. Sammut (ed. Proc of the 12th Int. Conf. on Inductive Logic Programming, ILP 2002, Sydney, Australia. 1 Introduction Carin was proposed by [ Levy and Rouset, 1998 ] as a combination of the two main approaches to represent and reason about relational knowledge, namely description logic (DL) and first order horn logic (HL) In Inductive Logic Programming (ILP) learning first order horn logic is investigated in depth, for learning DLs there exist first ....

....(#(C) C, i.e. it allows to retranslate generalized (i.e. learned) clauses: If D is a linked clause , and # I# #(C) for any description C, then # 1 (D) is totally invertible and produces a valid description logic term. 3 Induction of Description Logic Programs Carin as proposed in [ Levy and Rouset, 1998 ] combines first order functionfree horn logic with description logic by allowing description logic terms as body This gives a possibility to represent cyclic concept definitions from a terminological component in a finite way. However we haven t checked the adequate semantic interpretation ....

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Levy, A. Y. and M.-C. Rouset: 1998, `Combining horn rules and description logic in Carin'. Artificial Intelligence 104, 165--209.

.... basic progress has been made by establishing the theoretical foundations for the e#ective use of DL in DBs [7] DL o#er promising formalisms for solving several problems concerning conceptual data modelling (see, e.g. 12] intelligent information access and query processing (see, e.g. [8,34,9,24]) and information integration (see, e.g. 14,30,35,25] This Chapter will focus on conceptual modelling issues only. Conceptual modelling deals with the question on how to describe in a declarative and reusable way the domain information of an application, its relevant vocabulary, and how to ....

Alon Y. Levy and Marie-Christine Rousset. Combining horn rules and description logics in CARIN. Artificial Intelligence, 104(1-2):165--209, 1998.

....not only a theoretical result in a first experiment: learning Carin ALN rules from a standard ILP dataset. Extended version of a paper in S. Matwin, C. Sammut (ed. Proc of the 12th Int. Conf. on Inductive Logic Programming, ILP 2002, Sydney, Australia. 1 Introduction Carin was proposed by [ Levy and Rouset, 1998 ] as a combination of the two main approaches to represent and reason about relational knowledge, namely description logic (DL) and first order horn logic (HL) In Inductive Logic Programming (ILP) learning first order horn logic is investigated in depth, for learning DLs there exist first ....

....# 1 (#(C) C, i.e. it allows to decode generalized (i.e. learned) clauses: If D is a linked clause and D # I# #(C) for any description C, then # 1 (D) is totally invertible and produces a valid description logic term. 3 Induction of Description Logic Programs Carin as proposed in [ Levy and Rouset, 1998 ] combines first order functionfree horn logic with description logic by allowing description logic terms as body literals in horn rules. Concept terms represent unary predicates and role terms analysed this CLP extension of ILP systems and it is easy to see that the properties of # subsumption ....

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Levy, A. Y. and M.-C. Rouset: 1998, `Combining horn rules and description logic in Carin'. Artificial Intelligence 104, 165--209.

....us a preprocessing method, which enables ILP systems to learn Carin ALN rules just by transforming the data to be analyzed. We show, that this is not only a theoretical result in a first experiment: learning Carin ALN rules from a standard ILP dataset. 1 Introduction Carin was proposed by [ Levy and Rouset, 1998 ] as a combination of the two main approaches to represent and reason about relational knowledge, namely description logic (DL) and first order horn logic (HL) In Inductive Logic Programming (ILP) learning first order horn logic is investigated in depth, for learning DLs there exist first ....

.... 1 (#(C) C, i.e. it allows to decode generalized (i.e. learned) clauses: If D is a linked clause , and D # I# #(C) for any description C, then # 1 (D) is totally invertible and produces a valid description logic term. 3 Induction of Description Logic Programs Carin as proposed in [ Levy and Rouset, 1998 ] combines first order functionfree horn logic with description logic by allowing description logic terms as body literals in horn rules. Concept terms represent unary predicates and role terms represent binary predicates. The direct use of primitive concepts and roles is indistinguishable from ....

[Article contains additional citation context not shown here]

Levy, A. Y. and M.-C. Rouset: 1998, `Combining horn rules and description logic in Carin'. Artificial Intelligence 104, 165--209.

....for why propositionalisation approaches in general may outperform ILP or MRDM systems, as was sug gested before in the literature [Deroski et al. 1999] Srinivasan et al. 1999] Learning CARIN ALN rules with ILP methods 4. 1 Learning CARIN 4EAfas a pre processing method CARIN was proposed by [Levy and Rouser, 1998] as a combination of the two main approaches to represent and reason about relational knowledge, namely description logic and first order horn logic. In Inductive Logic Programming (ILP) learning first order horn logic is investigated in depth, for learning description logics there exist first ....

Levy, A. Y. and M.-C. Rouser: 1998, Combining horn rules and description logic in CARIN'. Artificial Intelligence 104, 165-209.

.... [28] Another idea is to deviate from the first order paradigm and start from computationally more friendly languages such as description logics which have been used in the area of non temporal information management to characterise in a uniform framework both conceptual modelling and queries [34, 12, 9, 10]. The temporal description logic DLRUS we devise in this paper is based on the expressive and decidable description logic DLR which allows the logical reconstruction and the extension of representational tools such as object oriented data models (e.g. class diagrams in UML and ODMG) semantic ....

A. Y. Levy and M-C. Rousset. Combining horn rules and description logics in CARIN. Artificial Intelligence, 104(1-2):165--209, 1998.

....possibilities, relaxations are generated in breadth first, and at each level, they are submitted to the user, who has to decide, interactively, which relaxation he prefers. The work we have presented should be extended in order to take into account the full expressiveness of the formalism CARIN [13], language used in the PICSEL project and which combines Horn rules with description logics. It could be interesting, first, to go further in exploiting the analogies with diagnosis, trying to map other algorithms [3] 4] and second, to investigate the links between our notion of generalisation ....

A. Levy and M.-C. Rousset. Combining Horn Rules and Description Logics in CARIN. In Artificial Intelligence, 104, 165-209, 98.

....(step) planning. From an abstract point of view, a language like Reiter s GOLOG language, which has been implemented on top of PROLOG, would provide sucient means for this purpose. This in turn would lead to the requirement of an A Box reasoning facility on the basis of Horn rules (cf. CARIN [16]) As a framework for processing partial information, we found out that FIL [1] meets all our requirements. We started with the implementation of a prover for a Horn clause subset of FIL in Prolog technology, which has later been replaced by a tableau based reasoner, operating as a separate ....

A.Y. Levy, M.-C. Rousset, Combining Horn rules and description logics in CARIN . Articial Intelligence Journal, Vol. 104, 1998, 165-209

....is NP complete. One interesting special case for which containment is tractable is when the right hand side query has bounded treewidth [25] and, in particular, when it is acyclic. Other papers consider the case of conjunctive query containment in the presence of various types of constraints [5, 28, 20, 40, 41, 12]. Conjunctive RPQs without inverse have been studied in [33] where an EXPSPACE algorithm for query containment in this class is presented. In [16] it is shown that containment for conjunctive two way regular path queries without constants is EXPSPACE complete. The complexity of query containment ....

A. Y. Levy and M.-C. Rousset. Combining horn rules and description logics in CARIN. Artificial Intelligence, 104(1--2):165--209, 1998.

....and for expressing website semantics in the next generation semantic web [5] Horn rules and descriptions logics are two orthogonal subsets of first order logic: it is known [6] that neither of these languages can express the other. Their combination has been studied in Al log [13] and in Carin [16]. In contrast, in this paper, we focus on the logical overlapping existing between conjunctive queries and concept descriptions. In our comparison, since description logics only deal with unary and binary relations, we restrict the conjunctive queries that we consider to be made of unary and ....

....ALE concept description. Theorem 2 Let C be a satisfiable ALEN concept description, and q a conjunctive query: If C q, then q or one of its restriction is a forest query. Sketch of proof: The full proof is given in [1] It is based on the completion calculus and reuses known results from [16]. In particular, since C q is equivalent to C(X) j= q(X) then for any clash free completion S of C(X) there exists a mapping ff from the variables appearing in q into the variables of S such that ff(X) X, if r(U1 ; U2 ) is in q then r(ff(U1) ff(U2) 2 S and if C(U) is in q then S j= ....

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A.Y. Levy and M-C. Rousset, `CombiningHorn Rules and Description Logics in Carin', Artificial Intelligence, 101, (1998).

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Alon Y. Levy and Marie-Christine Rousset. Combining horn rules and description logics in CARIN. Artificial Intelligence, 104:165--209, 1998.

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A. Y. Levy and M.-C. Rousset. Combining horn rules and description logics in CARIN. Artificial Intelligence, 104:165 -- 209, 1998.

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LEVY, A., AND ROUSSET, M.-C. Combining horn rules and description logics in carin. Artificial Intelligence 104(1-2) (1998), 165--209.

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A. Y. Levy and M.-C. Rousset. Combining horn rules and description logics in CARIN. Artificial Intelligence, 104:165 -- 209, 1998.

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A. Y. Levy and M.-C. Rousset. Combining Horn rules and description logics in CARIN. Artificial Intelligence, 104(1--2):165--209, 1998.

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A.Y. Levy and M-C. Rousset. Combining Horn Rules and Description Logics in CARIN. Artificial Intelligence , 104(1-2):165--209, 1998.

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Alon Y. Levy and Marie-Christine Rousset. Combining Horn rules and description logics in CARIN. Artificial Intelligence, 104(1--2):165--209, 1998.

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A. Levy and M.-C. Rousset, "Combining Horn rules and description logics in carin," Artificial Intelligence, vol. 104, pp. 165--209, September 1998.

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A. Levy and M. Rousset. Combining horn rules and description logics in CARIN. Artificial Intelligence Journal, 104, September 1998. 189

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A. Y. Levy and M.-C. Rousset. Combining Horn rules and description logics in CARIN. Artificial Intelligence, 104(1--2):165--209, 1998.

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A. Y. Levy and M.-C. Rousset. Combining Horn rules and description logics in CARIN. Artificial Intelligence, 104(1--2):165--209, 1998.

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A. Levy and M.-C. Rousset. Combining Horn rules and description logics in CARIN. Artificial Intelligence, 104:165--209, 1998.

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A. Y. Levy and M. Rousset, Combining Horn Rules and Description Logics in CARIN. In: Artificial Intelligence 104 (1-2), 165-209, 1998.

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A. Levy and M.-C. Rousset. Combining Horn rules and description logics in carin. Artificial Intelligence, 104:165--209, September 1998.

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